Photon-counting computed tomography versus energy-integrating computed tomography for detection of small liver lesions: comparison using a virtual framework imaging.

in silico liver lesions photon-counting computed tomography virtual trials

Journal

Journal of medical imaging (Bellingham, Wash.)
ISSN: 2329-4302
Titre abrégé: J Med Imaging (Bellingham)
Pays: United States
ID NLM: 101643461

Informations de publication

Date de publication:
Sep 2024
Historique:
received: 26 04 2024
revised: 03 09 2024
accepted: 23 09 2024
pmc-release: 17 10 2025
medline: 21 10 2024
pubmed: 21 10 2024
entrez: 21 10 2024
Statut: ppublish

Résumé

Photon-counting computed tomography (PCCT) has the potential to provide superior image quality to energy-integrating CT (EICT). We objectively compare PCCT to EICT for liver lesion detection. Fifty anthropomorphic, computational phantoms with inserted liver lesions were generated. Contrast-enhanced scans of each phantom were simulated at the portal venous phase. The acquisitions were done using DukeSim, a validated CT simulation platform. Scans were simulated at two dose levels ( Across all studied conditions, the best detection performance, measured by PCCT demonstrated objective improvement in liver lesion detection and image quality metrics compared with EICT. These advances may lead to earlier and more accurate liver lesion detection, thus improving patient care.

Identifiants

pubmed: 39430123
doi: 10.1117/1.JMI.11.5.053502
pii: 24125GR
pmc: PMC11486217
doi:

Types de publication

Journal Article

Langues

eng

Pagination

053502

Informations de copyright

© 2024 Society of Photo-Optical Instrumentation Engineers (SPIE).

Auteurs

Nicholas Felice (N)

Duke University, Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Durham, North Carolina, United States.
Duke University, Medical Physics Graduate Program, Durham, North Carolina, United States.

Benjamin Wildman-Tobriner (B)

Duke University, Department of Radiology, Durham, North Carolina, United States.

William Paul Segars (WP)

Duke University, Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Durham, North Carolina, United States.
Duke University, Medical Physics Graduate Program, Durham, North Carolina, United States.
Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States.

Mustafa R Bashir (MR)

Duke University, Department of Radiology, Durham, North Carolina, United States.

Daniele Marin (D)

Duke University, Department of Radiology, Durham, North Carolina, United States.

Ehsan Samei (E)

Duke University, Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Durham, North Carolina, United States.
Duke University, Medical Physics Graduate Program, Durham, North Carolina, United States.
Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States.
Duke University, Department of Electrical and Computer Engineering, Durham, North Carolina, United States.
Duke University, Department of Physics, Durham, North Carolina, United States.

Ehsan Abadi (E)

Duke University, Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Durham, North Carolina, United States.
Duke University, Medical Physics Graduate Program, Durham, North Carolina, United States.
Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States.

Classifications MeSH